1. Field of the Invention
The present invention relates to a maximum likelihood sequence estimation apparatus for use in digital data transmission.
2. Description of the Prior Art
A conventional maximum likelihood sequence estimation apparatus has been disclosed, for example, in the article "Adaptive Maximum-Likelihood Receiver for Carrier-Modulated Data-Transmission System", by G. Ungerboeck (IEEE Transactions on Communications, Vol. COM-22, No. 5, May 1974, pp. 624-634). In general the function of such an apparatus is to reliably receive data transmitted over a band-limited channel that is subject to intersymbol interference and noise.
FIG. 1 is a block diagram of such a conventional maximum likelihood sequence estimating apparatus.
In this figure, a maximum likelihood sequence estimation circuit 1, a channel impulse response (CIR) characteristic estimation circuit 4, a received signal input terminal 5, a decision data output terminal 6 and a fixed delay line 7 are indicated. Here, the maximum likelihood sequence estimation circuit 1 inputs a received demodulated data signal from the receiving signal input terminal 5 and an estimated channel characteristic from the channel impulse response characteristic estimation circuit 4, estimates the digital data sequence having the maximum probability of transmission using the Viterbi algorithm and outputs the estimated data sequence at the output terminal 6 depending on the amount of delay of a fixed delay line 7 having a previously determined delayed output. The channel impulse response characteristic estimation circuit 4 estimates a channel impulse response characteristic on the basis of the estimated data sequence outputted from the maximum likelihood sequence estimation circuit 1 and the output of fixed delay line 7 and outputs estimated values of the channel impulse response characteristic to the maximum likelihood sequence estimation circuit 1.
Next, operation of the conventional apparatus will be explained. When a received data signal is inputted to the maximum likelihood estimation circuit 1, this circuit operates as follows based on the channel impulse response characteristic estimated by the estimation circuit 4. Namely, it computes the probability of existence for each possible sequence "state" of the present time based on the probability of existence for each sequence "state" which has already been computed as to a received sequence in the past which is stored in memory. A sequence "state" refers to the state of the transmitter after a particular data sequence has been transmitted and determines which sequences can be further transmitted. The maximum likelihood estimation circuit 1 then chooses the most probable transition of states as "surviving paths" and outputs an estimated data sequence at data output terminal 6 when the surviving paths determined previously merge to a single path at a certain point in time in the past. The surviving paths and their probabilities are stored for each state.
The fixed delay line 7 outputs the received data signal having a fixed delay of the same quantity as the maximum likelihood sequence estimation circuit 1.
The channel impulse response characteristic estimation circuit 4 fetches the estimated data sequence from the maximum likelihood estimation circuit 1 and the received signal from the fixed delay line 7 to estimate the channel impulse response characteristic.
FIG. 2 is a circuit equivalent model of the channel impulse response of a channel including intersymbol interference. {I.sub.n } represents a transmitted data sequence of a certain length; {r.sub.n } represents a received data sequence. In the circuit model of this example, one sample of the transmitted signal I.sub.n-1 at time n-1 is stored in one sample delay unit 8, and one sample of the received signal r.sub.n is indicated as a sum of the current transmitted signal I.sub.n .times.f.sub.o and I.sub.n-1 .times.f.sub.1 (r.sub.n =f.sub.o I.sub.n +f.sub.1 I.sub.n-1). Here f.sub.0 and f.sub.1 are weighting factors which duplicate the impulse response of the channel.
For the channel impulse response characteristic estimation, the estimated data sequence of the transmitted signal generated at output terminal 6 is usually required. The characteristic estimation circuit 4 determines values for weighting factors f.sub.0 and f.sub.1 according to the amount of error between the estimated data sequence and the transmitted data sequence. As an example, the MSE (Mean Square Error) method will be explained hereunder.
Here, (n) is a point in time n, .DELTA. is an adjusting step size and q is an amount of "fixed delay". EQU f.sub.1 (n+1)=f.sub.i (n)+.DELTA.e(n-1)I.sub.n-i-q (i=0, 1) EQU e(n-q).times.r.sub.n-q -f.sub.o (pu n)I.sub.n-q -f.sub.1 (n)I.sub.n-1-q
where e=error between the transmitted signal and its estimated value. According to the MSE method, e is determined from the equation ##EQU1##
FIG. 3 is a trellis diagram for the case where 0 and 1 are given as the possible states of the transmitted signal sequence for the example of FIG. 2. In this example, the Viterbi algorithm which estimates the maximum likelihood sequence of state transitions can be expressed by providing 0 states and 1 states. The solid line in the figure means the final estimated data sequence and the intermediate surviving sequences are indicated by the dotted lines. Namely, the maximum likelihood estimated sequence of "10001" from time n-5 to time n-1 cannot be determined until time n when the transitions of both possible states "0" and "1" merge to state "1" at time n-1, where the previous merge time occurred at time n-4. Before this time, all surviving paths are still candidates for the finally determined estimated data sequence. Since at time n-1 the previous merge occurred at time n-4, the amount of fixed delay of the receiver must be set to at least 3. In practice, the maximum fixed delay is set to a mathematically determined value so that the probability of occurrence of merges having longer intervals is so small that it can be neglected.
The conventional maximum likelihood estimation apparatus described above is accompanied by a problem that tracking of the data for a time-varying channel impulse response characteristic is delayed where the final estimated data sequence is used for impulse response characteristic estimation because of the fixed delay amount required for final estimated data sequence determination.
For instance, in the above example, the impulse response estimation is delayed by three samples because the fixed delay q is set to 3. Moreover, in some cases, a larger quantity q must be used and as such, the channel impulse response characteristic estimation is further delayed.